Paper Citation Record · LEDGER

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design

As of 7 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2505.16335.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.16335 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:08:20.051805Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

verified exact2
verified fuzzy11
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 749ced13-3dd8-4b9c-8b04-e84adfaad212 · outbound

This paper cites Denoising diffusion probabilistic models,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Denoising diffusion probabilistic models,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:16.546335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42ef0fe9-6e3a-4823-afaf-7dd7f2829914 · outbound

This paper cites Denoising Diffusion Implicit Models.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Denoising Diffusion Implicit Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:16.655202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca859682-2594-4b8c-a523-e0d9014f729d · outbound

This paper cites Diffusion models beat gans on image synthesis,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Diffusion models beat gans on image synthesis,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:16.754219Z

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Unavailable: canonical work link unavailable.

Observation 49aaa801-155b-457e-a4a4-2a5f1212291d · outbound

This paper cites Scalable diffusion models with transformers,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Scalable diffusion models with transformers,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:16.850593Z

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Unavailable: canonical work link unavailable.

Observation 948185c9-b534-44f3-850a-89b534eb8e5e · outbound

This paper cites Generative pretraining from pixels,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Generative pretraining from pixels,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:16.926009Z

Source-reported events for the cited work

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Observation b997f128-7655-401b-9655-738edc6ba9fd · outbound

This paper cites Taming transformers for high- resolution image synthesis,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Taming transformers for high- resolution image synthesis,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:17.029079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7cd1404-6886-4767-942f-3e9965f0ff6e · outbound

This paper cites Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:17.128084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecd241b6-28b7-4243-9594-c46a2178edec · outbound

This paper cites Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:17.260819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5495676-b4c9-462e-9387-fd55ef344604 · outbound

This paper cites Visual autoregressive modeling: Scalable image generation via next-scale prediction,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Visual autoregressive modeling: Scalable image generation via next-scale prediction,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:17.404145Z

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Unavailable: canonical work link unavailable.

Observation 2504aae4-0fc2-4d08-93d0-220b45c71c45 · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Smoothquant: Accurate and efficient post-training quantization for large language models,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:17.523532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 842cd2aa-bc0b-43d7-a418-21ccc44cb6f0 · outbound

This paper cites Outlier suppression: Pushing the limit of low-bit transformer language models,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Outlier suppression: Pushing the limit of low-bit transformer language models,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:21.847122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d2995bb-9ddb-420c-92e6-81a8eb17fd90 · outbound

This paper cites Quarot: Outlier-free 4-bit inference in rotated llms,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Quarot: Outlier-free 4-bit inference in rotated llms,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:21.711521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 820dc867-c13e-42e8-9cdb-852d6d4c15a1 · outbound

This paper cites SpinQuant: LLM quantization with learned rotations.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design SpinQuant: LLM quantization with learned rotations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:17.931518Z

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Observation d5beb406-5726-4a24-9aad-e274f6b086a0 · outbound

This paper cites Q-diffusion: Quantizing diffusion models,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Q-diffusion: Quantizing diffusion models,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:21.493690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7dfa3911-17a7-48c2-ad53-5770668d2439 · outbound

This paper cites Temporal dynamic quanti- zation for diffusion models,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Temporal dynamic quanti- zation for diffusion models,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:21.372088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7f7a6b72-d101-4161-a237-b86f2f88b6d1 · outbound

This paper cites Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:18.124350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1676305-f776-4e6f-bc3a-19622365b281 · outbound

This paper cites PTQ4DiT: Post-training Quantization for Diffusion Transformers.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design PTQ4DiT: Post-training Quantization for Diffusion Transformers

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:18.201824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55003728-22df-4ba0-afaa-6ace648c0a4f · outbound

This paper cites LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design LiteVAR: Compressing Visual Autoregressive Modelling with Efficient Attention and Quantization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:18.268294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 097a2b6d-aa2b-49d6-87df-227ad1eb8fba · outbound

This paper cites Fp8 quantization: The power of the exponent,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Fp8 quantization: The power of the exponent,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:21.255069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2324a57e-820d-4a59-baf5-e5ffa36b689a · outbound

This paper cites LLM-FP4: 4-Bit Floating-Point Quantized Transformers.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:18.429756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34ba1823-ba22-4998-a4d9-5f5e61100281 · outbound

This paper cites Flightllm: Efficient large language model inference with a complete mapping flow on fpgas,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Flightllm: Efficient large language model inference with a complete mapping flow on fpgas,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:18.510325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c8a7b88-0f2b-41ef-a638-f05668ad4f36 · outbound

This paper cites Hg-pipe: Vision transformer acceleration with hybrid-grained pipeline,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Hg-pipe: Vision transformer acceleration with hybrid-grained pipeline,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:21.170408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f7629a5d-4c78-4c5b-8599-ad5cb7da9671 · outbound

This paper cites Flightvgm: Efficient video generation model inference with online sparsification and hybrid precision on fpgas,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Flightvgm: Efficient video generation model inference with online sparsification and hybrid precision on fpgas,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:21.091857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 273d2ffc-c62f-46cd-ba99-a9e7d72cf1d9 · outbound

This paper cites Pushing up to the Limit of Memory Bandwidth and Capacity Utilization for Efficient LLM Decoding on Embedded FPGA.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Pushing up to the Limit of Memory Bandwidth and Capacity Utilization for Efficient LLM Decoding on Embedded FPGA

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:08:20.471445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3339b255-1270-4a79-8207-d2347106f391 · outbound

This paper cites Generating diverse high- fidelity images with vq-vae-2,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Generating diverse high- fidelity images with vq-vae-2,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:20.940938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b08d09c7-aeab-4076-8a6f-85d58bb17a48 · outbound

This paper cites Autoregressive image generation using residual quantization,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Autoregressive image generation using residual quantization,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:18.812744Z

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Unavailable: canonical work link unavailable.

Observation 108bed22-11e9-40a9-9cb6-7f6f4c798f80 · outbound

This paper cites Movq: Modulating quantized vectors for high-fidelity image generation,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Movq: Modulating quantized vectors for high-fidelity image generation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:20.821626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 46c54b47-c171-4557-b14f-07ec036678ea · outbound

This paper cites Neural discrete representation learning,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Neural discrete representation learning,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:18.922830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3950bb1-72cb-414d-9b35-314a49817cc7 · outbound

This paper cites HART: Efficient Visual Generation with Hybrid Autoregressive Transformer.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design HART: Efficient Visual Generation with Hybrid Autoregressive Transformer

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:18.995473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2120a717-5a30-402a-8975-40b27df3a92b · outbound

This paper cites Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:19.064420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 433d04e1-67f5-4bed-8165-446a9874186a · outbound

This paper cites Integer or floating point? new outlooks for low- bit quantization on large language models,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Integer or floating point? new outlooks for low- bit quantization on large language models,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:20.741256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ef50f1ad-8011-40ab-8fd4-3d723c66ecc6 · outbound

This paper cites AFPQ: Asymmetric Floating Point Quantization for LLMs.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design AFPQ: Asymmetric Floating Point Quantization for LLMs

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:08:20.273869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 444f4fcb-02da-420c-a87a-076298c478fd · outbound

This paper cites Optimizing Large Language Model Training Using FP4 Quantization.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Optimizing Large Language Model Training Using FP4 Quantization

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:19.246282Z

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Unavailable: canonical work link unavailable.

Observation 889b3360-a0d1-49be-9c43-d9a2f099cc22 · outbound

This paper cites Microscaling Data Formats for Deep Learning.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Microscaling Data Formats for Deep Learning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:19.316349Z

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Unavailable: canonical work link unavailable.

Observation dd0a49a5-c605-456d-9499-78c7d673d2c7 · outbound

This paper cites Classifier-Free Diffusion Guidance.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Classifier-Free Diffusion Guidance

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:19.353900Z

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Unavailable: canonical work link unavailable.

Observation 0375a9da-d410-435d-b998-6a369bb05617 · outbound

This paper cites Sda: Low-bit stable diffusion acceleration on edge fpgas,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Sda: Low-bit stable diffusion acceleration on edge fpgas,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:08:20.638053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1701048e-5233-43b6-8373-ec0ed31119ab · outbound

This paper cites Lightmamba: Efficient mamba acceleration on fpga with quantization and hardware co-design,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Lightmamba: Efficient mamba acceleration on fpga with quantization and hardware co-design,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:19.504245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d15ddb6-f0cc-4634-a0e7-14388ecc0e4a · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:19.617528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83ec10a0-aad1-4b49-890e-1678d7fd1529 · outbound

This paper cites Improved techniques for training gans,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Improved techniques for training gans,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:19.713649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 194a1eb1-eb74-455e-9597-4104f656d3e1 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium,.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Gans trained by a two time-scale update rule converge to a local nash equilibrium,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:19.836325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b5304fc-870f-4c31-9cb0-fc83087b6b0a · outbound

This paper cites Decoupled Weight Decay Regularization.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design Decoupled Weight Decay Regularization

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:19.955333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c0b1c0a-3e90-4297-8665-9f4292d12b99 · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

FPQVAR: Floating Point Quantization for Visual Autoregressive Model with FPGA Hardware Co-design FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:20.051805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

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